Update app.py
Browse files
app.py
CHANGED
@@ -16,6 +16,41 @@ import os
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from datetime import datetime
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from gradio_client import Client
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def save_file(content, file_type):
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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file_name = f"{file_type}_{timestamp}.md"
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@@ -74,38 +109,6 @@ def main():
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import streamlit as st
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import streamlit.components.v1 as components
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import os
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import json
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import random
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import base64
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import glob
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import math
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import openai
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import pytz
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import re
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import requests
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import textract
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import time
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import zipfile
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import huggingface_hub
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import dotenv
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from audio_recorder_streamlit import audio_recorder
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from bs4 import BeautifulSoup
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from collections import deque
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from datetime import datetime
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from dotenv import load_dotenv
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from huggingface_hub import InferenceClient
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from io import BytesIO
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from openai import ChatCompletion
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from PyPDF2 import PdfReader
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from templates import bot_template, css, user_template
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from xml.etree import ElementTree as ET
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from PIL import Image
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from urllib.parse import quote # Ensure this import is included
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# Set page configuration with a title and favicon
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st.set_page_config(
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page_title="📖🔍WordGameAI",
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@@ -1209,7 +1212,7 @@ def StreamMedChatResponse(topic):
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# 17. Main
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def arxivmain():
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prompt = PromptPrefix2
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with st.expander("Prompts 📚", expanded=
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example_input = st.text_input("Enter your prompt text:", value=prompt, help="Enter text to get a response.")
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if st.button("Run Prompt", help="Click to run."):
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try:
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@@ -1276,7 +1279,7 @@ def get_audio_download_link(file_path):
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base64_file = get_base64_encoded_file(file_path)
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return f'<a href="data:file/wav;base64,{base64_file}" download="{os.path.basename(file_path)}">⬇️ Download Audio</a>'
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#
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all_files = glob.glob("*.wav")
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all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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@@ -1341,12 +1344,13 @@ except:
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st.markdown(' ')
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# Display the glossary grid
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st.markdown("### 🎲🗺️
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display_buttons_with_scores() # Feedback Jump Grid
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display_videos_and_links() # Video Jump Grid
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display_images_and_wikipedia_summaries() # Image Jump Grid
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if 'action' in st.query_params:
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@@ -1379,7 +1383,6 @@ if st.button("Clear Query Parameters", key='ClearQueryParams'):
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# 18. Run AI Pipeline
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if __name__ == "__main__":
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whisper_main()
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arxivmain()
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main()
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from datetime import datetime
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from gradio_client import Client
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import streamlit as st
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import streamlit.components.v1 as components
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import os
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import json
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import random
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import base64
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import glob
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import math
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import openai
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import pytz
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import re
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import requests
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import textract
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import time
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import zipfile
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import huggingface_hub
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import dotenv
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from audio_recorder_streamlit import audio_recorder
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from bs4 import BeautifulSoup
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from collections import deque
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from datetime import datetime
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from dotenv import load_dotenv
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from huggingface_hub import InferenceClient
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from io import BytesIO
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from openai import ChatCompletion
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from PyPDF2 import PdfReader
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from templates import bot_template, css, user_template
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from xml.etree import ElementTree as ET
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from PIL import Image
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from urllib.parse import quote # Ensure this import is included
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def save_file(content, file_type):
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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file_name = f"{file_type}_{timestamp}.md"
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# Set page configuration with a title and favicon
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st.set_page_config(
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page_title="📖🔍WordGameAI",
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# 17. Main
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def arxivmain():
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prompt = PromptPrefix2
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with st.expander("Prompts 📚", expanded=True):
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example_input = st.text_input("Enter your prompt text:", value=prompt, help="Enter text to get a response.")
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if st.button("Run Prompt", help="Click to run."):
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try:
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base64_file = get_base64_encoded_file(file_path)
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return f'<a href="data:file/wav;base64,{base64_file}" download="{os.path.basename(file_path)}">⬇️ Download Audio</a>'
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# Sidebar of past encounters
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all_files = glob.glob("*.wav")
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all_files = [file for file in all_files if len(os.path.splitext(file)[0]) >= 10] # exclude files with short names
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all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) # sort by file type and file name in descending order
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st.markdown(' ')
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# Display the glossary grid
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st.markdown("### 🎲🗺️ Arxiv Paper Search QA RAG MAS using Streamlit and Gradio API")
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arxivmain()
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display_videos_and_links() # Video Jump Grid
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display_images_and_wikipedia_summaries() # Image Jump Grid
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display_glossary_grid(roleplaying_glossary) # Word Glossary Jump Grid
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#display_buttons_with_scores() # Feedback Jump Grid
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if 'action' in st.query_params:
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# 18. Run AI Pipeline
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if __name__ == "__main__":
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whisper_main()
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main()
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